Over the past decades, unsupervised domain adaptation (UDA) has attracted extensive research attention [1]}. Numerous UDA methods have been proposed and successfully applied to various real-world applications, e.g., object recognition [2]}, [3]}, [4]}, semantic segmentation [5]}, [6]}, [7]}, and object detection [8]}, [9]}, [10]}.
However, most of these methods and their applications are limited to the image domain, while much less attention has been devoted to video-based UDA, where the latter is undoubtedly more challenging.
